Train and Test Accuracy of GRU network not increasing after 2nd epoch
Couple reccomendations:
1) I dont think your overfitting, your test loss is not ever increasing and is staying reasonbly proportional to train loss -- This may indicate that whatever loss your using is not a good indicator of the metric of interest (in this case, it seems you want that to be accuracy, but data is imbalnced so maybe look at avg precision?)
2) Use a lr scheduler, or something like a ReduceLROnPlateau callback to reduce the lr once the loss converges
3) Adding more sources of the underrepresented class is valid but i reccomend just using class weighting. Effectively its the same (as an expectation) and will save you train time.  

Good Luck!